Taguchi-based grey relational analysis for modeling and optimizing machining parameters through dry turning of Incoloy 800H

Abstract

The present research focused on the optimization of machining parameters and their effects by dry-turning an incoloy 800H on the basis of Taguchi-based grey relational analysis. Surface roughness (Ra, Rq and Rz), cutting force (Fz), and cutting power (P) were minimized, whereas Material removal rate (MRR) was maximized. An L 27 orthogonal array was used in the experiments, which were conducted in a computerized and numerical-controlled turning machine. Cutting speed, feed rate, and cut depth were set as controllable machining variables, and analysis of variance was performed to determine the contribution of each variable. We then developed regression models, which ultimately conformed to investigational and predicted values. The combinational parameters for the multiperformance optimization were V = 35 m/min, f = 0.06 mm/rev and a = 1 mm, which altogether correspond to approximately 48.98 % of the improvement. The chip morphology of the incoloy 800H was also studied and reported.